Literature DB >> 29264866

Mapping the Paediatric Quality of Life Inventory (PedsQL™) Generic Core Scales onto the Child Health Utility Index-9 Dimension (CHU-9D) Score for Economic Evaluation in Children.

Tosin Lambe1, Emma Frew2, Natalie J Ives3, Rebecca L Woolley3, Carole Cummins4, Elizabeth A Brettell3, Emma N Barsoum3, Nicholas J A Webb5.   

Abstract

BACKGROUND: The Paediatric Quality of Life Inventory (PedsQL™) questionnaire is a widely used, generic instrument designed for measuring health-related quality of life (HRQoL); however, it is not preference-based and therefore not suitable for cost-utility analysis. The Child Health Utility Index-9 Dimension (CHU-9D), however, is a preference-based instrument that has been primarily developed to support cost-utility analysis.
OBJECTIVE: This paper presents a method for estimating CHU-9D index scores from responses to the PedsQL™ using data from a randomised controlled trial of prednisolone therapy for treatment of childhood corticosteroid-sensitive nephrotic syndrome.
METHODS: HRQoL data were collected from children at randomisation, week 16, and months 12, 18, 24, 36 and 48. Observations on children aged 5 years and older were pooled across all data collection timepoints and were then randomised into an estimation (n = 279) and validation (n = 284) sample. A number of models were developed using the estimation data before internal validation. The best model was chosen using multi-stage selection criteria.
RESULTS: Most of the models developed accurately predicted the CHU-9D mean index score. The best performing model was a generalised linear model (mean absolute error = 0.0408; mean square error = 0.0035). The proportion of index scores deviating from the observed scores by <  0.03 was 53%.
CONCLUSIONS: The mapping algorithm provides an empirical tool for estimating CHU-9D index scores and for conducting cost-utility analyses within clinical studies that have only collected PedsQL™ data. It is valid for children aged 5 years or older. Caution should be exercised when using this with children younger than 5 years, older adolescents (>  13 years) or patient groups with particularly poor quality of life. ISRCTN REGISTRY NO: 16645249.

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Year:  2018        PMID: 29264866     DOI: 10.1007/s40273-017-0600-7

Source DB:  PubMed          Journal:  Pharmacoeconomics        ISSN: 1170-7690            Impact factor:   4.981


  33 in total

Review 1.  Generic and disease-specific measures in assessing health status and quality of life.

Authors:  D L Patrick; R A Deyo
Journal:  Med Care       Date:  1989-03       Impact factor: 2.983

2.  Working with children to develop dimensions for a preference-based, generic, pediatric, health-related quality-of-life measure.

Authors:  Katherine J Stevens
Journal:  Qual Health Res       Date:  2010-01-06

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Authors:  Nalin Payakachat; Kent H Summers; Andreas M Pleil; Matthew M Murawski; Joseph Thomas; Kristofer Jennings; James G Anderson
Journal:  Qual Life Res       Date:  2009-06-19       Impact factor: 4.147

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Authors:  A Mehrez; A Gafni
Journal:  Med Decis Making       Date:  1989 Apr-Jun       Impact factor: 2.583

5.  Measuring and valuing health benefits for economic evaluation in adolescence: an assessment of the practicality and validity of the child health utility 9D in the Australian adolescent population.

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6.  Assessing the calibration of mortality benchmarks in critical care: The Hosmer-Lemeshow test revisited.

Authors:  Andrew A Kramer; Jack E Zimmerman
Journal:  Crit Care Med       Date:  2007-09       Impact factor: 7.598

7.  The PedsQL 4.0 as a pediatric population health measure: feasibility, reliability, and validity.

Authors:  James W Varni; Tasha M Burwinkle; Michael Seid; Douglas Skarr
Journal:  Ambul Pediatr       Date:  2003 Nov-Dec

8.  A cluster-randomised controlled trial to assess the effectiveness and cost-effectiveness of a childhood obesity prevention programme delivered through schools, targeting 6-7 year old children: the WAVES study protocol.

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Review 9.  Review of studies mapping from quality of life or clinical measures to EQ-5D: an online database.

Authors:  Helen Dakin
Journal:  Health Qual Life Outcomes       Date:  2013-09-05       Impact factor: 3.186

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  8 in total

1.  Comment on: "Mapping the Paediatric Quality of Life Inventory (PedsQL™) Generic Core Scales Onto the Child Health Utility Index-9 Dimension (CHU-9D) Score for Economic Evaluation in Children".

Authors:  Emma Frew; Tosin Lambe
Journal:  Pharmacoeconomics       Date:  2018-08       Impact factor: 4.981

2.  Mapping the PedsQL™ onto the CHU9D: An Assessment of External Validity in a Large Community-Based Sample.

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4.  Economic Evaluation of Using Daily Prednisolone versus Placebo at the Time of an Upper Respiratory Tract Infection for the Management of Children with Steroid-Sensitive Nephrotic Syndrome: A Model-Based Analysis.

Authors:  Nafsika Afentou; Emma Frew; Samir Mehta; Natalie J Ives; Rebecca L Woolley; Elizabeth A Brettell; Adam R Khan; David V Milford; Detlef Bockenhauer; Moin A Saleem; Angela S Hall; Ania Koziell; Heather Maxwell; Shivaram Hegde; Eric Finlay; Rodney D Gilbert; Caroline Jones; Karl McKeever; Wendy Cook; Nicholas J A Webb; Martin T Christian
Journal:  Pharmacoecon Open       Date:  2022-06-22

5.  Priorities among effective clinical preventive services in British Columbia, Canada.

Authors:  Hans Krueger; Sylvia Robinson; Trevor Hancock; Richard Birtwhistle; Jane A Buxton; Bonnie Henry; Jennifer Scarr; John J Spinelli
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6.  Mapping PedsQLTM scores onto CHU9D utility scores: estimation, validation and a comparison of alternative instrument versions.

Authors:  Rohan Sweeney; Gang Chen; Lisa Gold; Fiona Mensah; Melissa Wake
Journal:  Qual Life Res       Date:  2019-11-19       Impact factor: 4.147

7.  An Assessment of the Validity and Reliability of the Pediatric Child Health Utility 9D in Children with Inflammatory Bowel Disease.

Authors:  Naazish S Bashir; Thomas D Walters; Anne M Griffiths; Wendy J Ungar
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